Portfolio Return Analysis with Bootstrapping

Forecasting future portfolio performance is a delicate topic, often not discussed in detail, more often it is quickly followed by a disclaimer – “past performance may not be indicative of future results”.

But, no matter the process historical performance of stocks, bonds, and other assets is a required input for forecasts. History repeats. So, is there a better way to evaluate historical performance?

One common pitfall is an assumption that returns are normally distributed. Unfortunately, unlikely events that negatively impact the markets and our portfolios happen all too often. The other naivety is that the relationship amongst asset class returns are constant. In reality, there is tendency for assets to move together in times of crisis. For example, in 2008 the S&P 500, DAX, S&P/TSX Composite, and Nikkei all lost in excess 30%, in local currency terms.

For a more accurate representation of what future portfolio returns may, or may not be, we employ a statistical technique that relies on random sampling with replacement – commonly referred to as bootstrapping. The backbone of this approach is to use raw historical data, without the assumption of normally distributed returns or linear co-variance. Historical returns are simulated several thousand times and from here average portfolio performance is established.